brain-computer interfaces
DESCRIPTION
Aim of a brain-computer interface (BCI) is to provide a communication channel for paralyzed patients to interact with the outer world. I will start with the motivation behind brain-computer interfaces followed by description of a general BCI. I will then describe various kinds of BCI experiments and methods.From the Un-Distinguished Lecture Series (http://ws.cs.ubc.ca/~udls/). The talk was given Jun. 8, 2007.TRANSCRIPT
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An overview of Brain-Computer Interface
Emtiyaz
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Brain Computer Interfacehttp://www.youtube.com/watch?v=NIG47YgndP8
http://www.youtube.com/watch?v=qCSSBEXBCbY
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ElectroEncephaloGram (EEG)• Hans Berger (1929)
– It is out of the question that the α-w and β-w of my EEG exert any effect at a distance; they can not be transmitted through space. Upon the advice of experienced electrophysicists, I refrained from any attempt to observe possible distant effects.
Photographs http://www.crossroadsinstitute.org/eeg.html and http://www.cs.colostate.edu/eeg/index.html
θ (4-8 Hz)δ (0.1 to 3 Hz) α (8-12 Hz) β(above 12 Hz)
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Why BCI?• Patients with neuromuscular disorders
– ALS, multiple sclerosis• Solutions
– Use the capabilities of remaining pathways– Detour around the points of damage– Provide the brain with new channels for communication control
Photographs Bayliss’ thesis 2000 and Pfurtscheller et.al.2002
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A general Brain-Computer Interface
Not reading thoughts, rather enforce subjects to certainmental states which can be recognized by the machine
Invasive/ Non-invasive
Different Features
Design of Experiments
Photographs from McFarland et.al. 2002
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P300 BCI
Photographs from http://www.gtec.at/products/g.BCIsys/bci.htmBayliss’s thesis 2000
Video : Spelling devices with P300http://www.youtube.com/watch?v=NlUPFpZswJk
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ERD and ERSEvent Related Desynchronization /Synchronization is an amplitude attenuation/ enhancement in the specific frequency bands associated with an event.
Frequency dependent
Left rightdifference
Photographs from Pfurscheller 2002
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Why Movements related imaginations?
Photographs from Kendel 1991
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ERD/ERS BCI ExperimentsTraining sessions
Testing sessions
Photographs from Pfurtscheller 1999
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Inter-trial Variance (IV) Method
Photographs from Pfurtscheller 1998
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RLS ApproachAdaptive Autoregressive (AAR) Model
Solved with Recursive least square (RLS) algorithms and features classified with Linear Discriminant Analysis (LDA)
observation noise
Photographs from Pfurtscheller 2000
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Direct Brain Interface
Photographs from http://www.gtec.at/products/g.BCIsys/bci.htm
Head of Florian D.